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Performance Characterization and Optimizations of Traditional ML Applications
Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization ...
Inverse Problems in 3D Full-wave Electromagnetics
An inverse problem in Electromagnetics (EM) refers to the process of reconstructing the physical system by processing the measured data of its electromagnetic properties. Inverse problems are typically ill-posed, and this ...
Novel First-order Algorithms for Non-smooth Optimization Problems in Machine Learning
This thesis is devoted to designing efficient optimization algorithms for machine learning (ML) problems where the underlying objective function to be optimized is convex but not necessarily differentiable. Such non-smooth ...
Low Power Machine Learning Systems for Energy Efficient Edge Devices
Energy-efficient devices are essential in the world of edge computing and the tiny Machine
Learning (tinyML) paradigm. Edge devices are often constrained by the available compu-
tational power and hardware resource. To ...
Boolean Functional Synthesis using Gated Continuous Logic Networks
Boolean Functional Synthesis (BFS) is a well-known challenging problem in the domain of automated program synthesis from logical specifications. This problem aims to synthesize a Boolean function that is correct-by-construction ...
Representing Networks: Centrality, Node Embeddings, Community Outliers and Graph Representation
Networks are ubiquitous. We start our technical work in this thesis by exploring the classical concept of node centrality (also known as influence measure) in information networks. Like clustering, node centrality is also ...
Temporal Point Processes for Forecasting Events in Higher-Order Networks
Real-world systems consisting of interacting entities can be effectively represented as time-evolving networks or graphs, where the entities are depicted as nodes, and the interactions between them are represented as ...
Investigating Neural Mechanisms of Word Learning and Speech Perception
Language learning and speech perception are remarkable feats performed by the human brain, involving complex neural mechanisms that allow us to understand and communicate with one another. Unravelling the mysteries of these ...